Perinatal EpidemiologyUnderstanding Etiologic Pathways Through Multiple Sequential Mediators: An Application in Perinatal EpidemiologyAnanth, Cande V.a–d; Loh, Wen Weie Author Information From the aDepartment of Obstetrics, Gynecology and Reproductive Sciences, and Department of Medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ bDepartment of Biostatistics and Epidemiology, Rutgers School of Public Health, Piscataway, NJ cCardiovascular Institute of New Jersey, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ dEnvironmental and Occupational Health Sciences Institute (EOHSI), Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ eDepartment of Data Analysis, Ghent University, Gent, Belgium. Editor’s Note: A related article appears on p. 864–867. Submitted May 3, 2021; accepted June 17, 2022 C.V.A. is partially supported by grants from the National Heart, Lung, and Blood Institute (R01-HL150065) and the National Institute for Environmental Health Sciences (R01-ES033190) of the National Institutes of Health. W.W.L. was supported by the Special Research Fund (BOF) of Ghent University postdoctoral fellowship BOF.PDO.2020.0045.01. The data used in this study are publicly available at https://www.cdc.gov/nchs/data_access/vitalstatsonline.htm. The R scripts implementing the estimation procedure are available online at https://github.com/wwloh/perinatal-multiple-mediation. The authors report no conflicts of interest. Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com). Correspondence: Cande V. Ananth, Division of Epidemiology and Biostatistics, Department of Obstetrics, Gynecology and Reproductive Sciences, Rutgers University, Robert Wood Johnson Medical School, 125 Paterson Street, New Brunswick, NJ 08901. E-mail: [email protected]. Epidemiology: November 2022 - Volume 33 - Issue 6 - p 854-863 doi: 10.1097/EDE.0000000000001518 Buy SDC Metrics Abstract Background: Causal mediation analysis facilitates decomposing the total effect into a direct effect and an indirect effect that operates through an intermediate variable. Recent developments in causal mediation analysis have clarified the process of evaluating how—and to what extent—different pathways via multiple causally ordered mediators link the exposure to the outcome. Methods: Through an application of natural effect models for multiple mediators, we show how placental abruption might affect perinatal mortality using small for gestational age (SGA) birth and preterm delivery as two sequential mediators. We describe methods to disentangle the total effect into the proportions mediated via each of the sequential mediators, when evaluating natural direct and natural indirect effects. Results: Under the assumption that SGA births causally precedes preterm delivery, an analysis of 16.7 million singleton pregnancies is consistent with the hypothesis that abruption exerts powerful effects on perinatal mortality (adjusted risk ratio = 11.9; 95% confidence interval = 11.6, 12.1). The proportions of the estimated total effect mediated through SGA birth and preterm delivery were 2% and 58%, respectively. The proportion unmediated via either SGA or preterm delivery was 41%. Conclusions: Through an application of causal mediation analysis with sequential mediators, we uncovered new insights into the pathways along which abruption impacts perinatal mortality. Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.